Now don't get me wrong, using sums violates 2 personally held beliefs...

1. Each position in a combo is as random and independent as previous draws.

2. The numbers have no numeric properties, they could have easily used A to J as 0 to 9.

But thinking about sums... a range from 0 (000) to 27 (999) that encompasses all 1,000 combinations.

A bell (Gaussian) curve over the distribution history, with sum 13 and sum 14 at the top of the curve. In contrast to the discrete uniform distribution created by taking pure frequency.

A one to many mapping, meaning many combos at the highest peaks.

Just like the digits themselves have no memory, the sums are just as random.

So, what use could they be?

My neutral selection process could have completely different neutrals in 150 draws, or even as soon as the next week. As I recently ran a full back test on the entire history, it might be worth a look to see what the observed sum range is. A tool to be used to help with the per column synchronization problem I have in all such systems. Roughly 10% of the data presents itself as all neutral in a back test, so that would be 1,700 sum samples to look at. Is there a range in which most would sit? Would any ranges NOT be present?

The aggregation of odd and even or high and low would still be per column and not of much use, but the sum could include a third group of statistic, we have per sample and per digit, this would be per draw... used on the observed history it could provide a loose guideline to apply when selecting from each category, which ones fall into a common sum range?

Of course any such constraint increases the chance of throwing away the winning combos, but all systems seem to do that even if it was not intentional.

Might be worth the look...

Turns out, in the last 94 neutral draws, 70 were within the sum range of sum 8 to sum 18, with the highest concentration between sum 11 and sum 16. That is interesting but not directly applicable.